Rust для машинного обучения - библиотека: различия между версиями

Материал из support.qbpro.ru
 
(не показаны 63 промежуточные версии этого же участника)
Строка 20: Строка 20:
* '''Jupyter Notebook'''
* '''Jupyter Notebook'''


* '''evcxr''' может обрабатывать как '''Jupyter Kernel''' или '''REPL'''. Эти библиотеки нужны для обучения алгоритмов и проверки гипотез машинного обучения.
* '''evcxr''' может обрабатывать как '''Jupyter Kernel''' или '''REPL'''.<br>
Эти библиотеки нужны для обучения алгоритмов и проверки гипотез машинного обучения.


* [https://github.com/google/evcxr google/evcxr - оценки моделей для Rust.]
* [https://github.com/google/evcxr google/evcxr - оценки моделей для Rust.]
Строка 58: Строка 59:
* [https://datacrayon.com/posts/programming/rust-notebooks/preface/ Preface | Data Crayon]<br>
* [https://datacrayon.com/posts/programming/rust-notebooks/preface/ Preface | Data Crayon]<br>
<br>
<br>
* '''Датафреймы''':<br>
* '''Дата-фреймы''':<br>
<hr>
<hr>
* [https://github.com/ritchie46/polars ritchie46/polars - Rust датафреймы library]<br>
* [https://github.com/ritchie46/polars ritchie46/polars - Rust датафреймы library]<br>
Строка 100: Строка 101:
* [https://github.com/Daniel-Liu-c0deb0t/uwu Daniel-Liu-c0deb0t/uwu - fastest text uwuifier in the west]<br>
* [https://github.com/Daniel-Liu-c0deb0t/uwu Daniel-Liu-c0deb0t/uwu - fastest text uwuifier in the west]<br>


==Графы==
==ГРАФЫ==
alibaba/GraphScope - GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba
* [https://github.com/alibaba/GraphScopealibaba/GraphScope GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba]<br>
petgraph/petgraph - Graph data structure library for Rust.
* [https://github.com/petgraph/petgraph petgraph/petgraph Graph data structure library for Rust.]<br>
rs-graph/rs-graph - rs-graph is a library for graph algorithms and combinatorial optimization
* [https://chiselapp.com/user/fifr/repository/rs-graph/doc/release/README.md rs-graph/rs-graph - rs-graph is a library for graph algorithms and combinatorial optimization]<br>
metamolecular/gamma - A graph library for Rust.
* [https://github.com/metamolecular/gamma metamolecular/gamma A graph library for Rust.]<br>
purpleprotocol/graphlib - Simple but powerful graph library for Rust
* [https://github.com/purpleprotocol/graphlib purpleprotocol/graphlib Simple but powerful graph library for Rust]<br>
yamafaktory/hypergraph - Hypergraph is a data structure library to generate directed hypergraphs
* [https://github.com/yamafaktory/hypergraph yamafaktory/hypergraph Hypergraph is a data structure library to generate directed hypergraphs]<br>


==AutoML==
==AutoML==
tangramxyz/tangram - Tangram is an all-in-one automated machine learning framework. https://github.com/tangramxyz/tangram
* [https://github.com/tangramxyz/tangram tangramxyz/tangram - Tangram is an all-in-one automated machine learning framework.]<br>
datafuselabs/datafuse - A Modern Real-Time Data Processing & Analytics DBMS with Cloud-Native Architecture, written in Rust
* [https://github.com/datafuselabs/datafuse datafuselabs/datafuse - A Modern Real-Time Data Processing & Analytics DBMS with Cloud-Native Architecture (Rust)]<br>
mstallmo/tensorrt-rs - Rust library for running TensorRT accelerated deep learning models
* [https://github.com/mstallmo/tensorrt-rs mstallmo/tensorrt-rs - Rust library for running TensorRT accelerated deep learning models]<br>
pipehappy1/tensorboard-rs - Write TensorBoard events in Rust.
* [https://github.com/pipehappy1/tensorboard-rs pipehappy1/tensorboard-rs - Write TensorBoard events in Rust.]<br>
ehsanmok/tvm-rust - Rust bindings for TVM runtime
* [https://github.com/ehsanmok/tvm-rust ehsanmok/tvm-rust - Rust bindings for TVM runtime]<br>
vertexclique/orkhon - Orkhon: ML Inference Framework and Server Runtime
* [https://github.com/vertexclique/orkhon vertexclique/orkhon - Orkhon: ML Inference Framework and Server Runtime]<br>
xaynetwork/xaynet - Xaynet represents an agnostic Federated Machine Learning framework to build privacy-preserving AI applications
* [https://github.com/xaynetwork/xaynet Xaynet represents an agnostic Federated Machine Learning framework to build privacy-preserving AI applications]<br>
webonnx/wonnx - A GPU-accelerated ONNX inference run-time written 100% in Rust, ready for the web
* [https://github.com/webonnx/wonnx webonnx/wonnx - A GPU-accelerated ONNX inference run-time written 100% in Rust, ready for the web]<br>
sonos/tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference
* [https://github.com/sonos/tract sonos/tract - Tiny, no-nonsense, self-contained, Tensorflow and ONNX inference]<br>
MegEngine/MegFlow - Efficient ML solutions for long-tailed demands
* [https://github.com/MegEngine/MegFlow MegEngine/MegFlow - Efficient ML solutions for long-tailed demands]<br>


==Рабочие потоки==
==РАБОЧИЕ ПОТОКИ==
substantic/rain - Framework for large distributed pipelines
* [https://github.com/substantic/rain substantic/rain - Framework for large distributed pipelines]<br>
timberio/vector - A high-performance, highly reliable, observability data pipeline
* [https://github.com/timberio/vector timberio/vector - A high-performance, highly reliable, observability data pipeline]<br>


==ГПУ==
==ВЫЧИСЛЕНИЯ НА GPU С ПОМОЩЬЮ RUST==
Rust-GPU/Rust-CUDA - Ecosystem of libraries and tools for writing and executing extremely fast GPU code fully in Rust.
* [https://github.com/Rust-GPU/Rust-CUDA Rust-GPU/Rust-CUDA - Ecosystem of libraries and tools for writing and executing extremely fast GPU code fully in Rust.]<br>
EmbarkStudios/rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU code 🚧
* [https://github.com/EmbarkStudios/rust-gpu EmbarkStudios/rust-gpu Making Rust a first-class language and ecosystem for GPU code]<br>
termoshtt/accel - GPGPU Framework for Rust
* [https://github.com/termoshtt/accel termoshtt/accel GPGPU Framework for Rust]<br>
kmcallister/glassful - Rust-like syntax for OpenGL Shading Language
* [https://github.com/kmcallister/glassful kmcallister/glassful Rust-like syntax for OpenGL Shading Language]<br>
MaikKlein/rlsl - Rust to SPIR-V compiler
* [https://github.com/MaikKlein/rlslMaikKlein/rlsl Rust to SPIR-V compiler]<br>
japaric-archived/nvptx - How to: Run Rust code on your NVIDIA GPU
* [https://github.com/japaric-archived/nvptx japaric-archived/nvptx - How to: Run Rust code on your NVIDIA GPU]<br>
msiglreith/inspirv-rust - Rust (MIR) → SPIR-V (Shader) compiler
* [https://github.com/msiglreith/inspirv-rust msiglreith/inspirv-rust Rust (MIR) → SPIR-V (Shader) compiler]<br>


==sklearn - подобные библиотеки==
==SKLEARN И ПОДОБНЫЕ БИБЛИОТЕКИ==
Библиотеки поддерживают следующие алгоритмы.
* Библиотеки поддерживают следующие алгоритмы:


Linear Regression
Linear Regression
Logistic Regression
Logistic Regression
K-Means Clustering
K-Means Clustering
Neural Networks
Neural Networks
Gaussian Process Regression
Gaussian Process Regression
Support Vector Machines
Support Vector Machines
kGaussian Mixture Models
kGaussian Mixture Models
Naive Bayes Classifiers
Naive Bayes Classifiers
DBSCAN
DBSCAN
k-Nearest Neighbor Classifiers
k-Nearest Neighbor Classifiers
Principal Component Analysis
Principal Component Analysis
Decision Tree
Decision Tree
Support Vector Machines
Support Vector Machines
Naive Bayes
Naive Bayes
Elastic Net
Elastic Net


smartcorelib/smartcore - SmartCore is a comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.LASSO, Ridge, Random Forest, LU, QR, SVD, EVD, and more metrics
* [https://github.com/smartcorelib/smartcore smartcorelib/smartcore - SmartCore is a comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.LASSO, Ridge, Random Forest, LU, QR, SVD, EVD, and more metrics]<br>
https://smartcorelib.org/user_guide/quick_start.html


rust-ml/linfa - A Rust machine learning framework.Gaussian Mixture Model Clustering, Agglomerative Hierarchical Clustering, ICA
* [https://github.com/rust-ml/linfa rust-ml/linfa - A Rust machine learning framework.Gaussian Mixture Model Clustering, Agglomerative Hierarchical Clustering, ICA]<br>
https://github.com/rust-ml/linfa#current-state
* [https://github.com/maciejkula/rustlearn maciejkula/rustlearn - Machine learning crate for Rustfactorization machines, k-fold cross-validation, ndcg]<br>
maciejkula/rustlearn - Machine learning crate for Rustfactorization machines, k-fold cross-validation, ndcg
https://github.com/maciejkula/rustlearn#features
AtheMathmo/rusty-machine - Machine Learning library for RustConfusion Matrix, Cross Varidation, Accuracy, F1 Score, MSE
https://github.com/AtheMathmo/rusty-machine#machine-learning
benjarison/eval-metrics - Evaluation metrics for machine learningMany evaluation functions
blue-yonder/vikos - A machine learning library for supervised training of parametrized models
mbillingr/openml-rust - A rust interface to http://openml.org/


==Статистика==
* [https://github.com/AtheMathmo/rusty-machine AtheMathmo/rusty-machine - Machine Learning library for RustConfusion Matrix, Cross Varidation, Accuracy, F1 Score, MSE]<br>
statrs-dev/statrs - Statistical computation library for Rust
rust-ndarray/ndarray-stats - Statistical routines for ndarray
Axect/Peroxide - Rust numeric library with R, MATLAB & Python syntaxLinear Algebra, Functional Programming, Automatic Differentiation, Numerical Analysis, Statistics, Special functions, Plotting, Dataframe
tarcieri/micromath - Embedded Rust arithmetic, 2D/3D vector, and statistics library


==Градиентный Бустинг==
* [https://github.com/benjarison/eval-metrics benjarison/eval-metrics - Evaluation metrics for machine learningMany evaluation functions]<br>
mesalock-linux/gbdt-rs - MesaTEE GBDT-RS : a fast and secure GBDT library, supporting TEEs such as Intel SGX and ARM TrustZone
davechallis/rust-xgboost - Rust bindings for XGBoost.
vaaaaanquish/lightgbm-rs - LightGBM Rust binding
catboost/catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks (predict only)
Entscheider/stamm - Generic decision trees for rust


==Нейронные сети==
* [https://github.com/blue-yonder/vikos blue-yonder/vikos - A machine learning library for supervised training of parametrized models]<br>
Tensorflow и PyTorch являются наиболее распространенными либами для построения нейронных сетей.


tensorflow/rust - Rust language bindings for TensorFlow
* [https://github.com/mbillingr/openml-rust mbillingr/openml-rust - A rust interface to http://openml.org/]<br>
LaurentMazare/tch-rs - Rust bindings for the C++ api of PyTorch.
VasanthakumarV/einops - Simplistic API for deep learning tensor operations
spearow/juice - The Hacker's Machine Learning Engine
neuronika/neuronika - Tensors and dynamic neural networks in pure Rust.
bilal2vec/L2 - l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust
raskr/rust-autograd - Tensors and differentiable operations (like TensorFlow) in Rust
charles-r-earp/autograph - Machine Learning Library for Rust
patricksongzy/corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.
JonathanWoollett-Light/cogent - Simple neural network library for classification written in Rust.
oliverfunk/darknet-rs - Rust bindings for darknet
jakelee8/mxnet-rs - mxnet for Rust
jramapuram/hal - Rust based Cross-GPU Machine Learning
primitiv/primitiv-rust - Rust binding of primitiv
chantera/dynet-rs - The Rust Language Bindings for DyNet
millardjn/alumina - A deep learning library for rust
jramapuram/hal - Rust based Cross-GPU Machine Learning
afck/fann-rs - Rust wrapper for the Fast Artificial Neural Network library
autumnai/leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU)
c0dearm/mushin - Compile-time creation of neural networks
tedsta/deeplearn-rs - Neural networks in Rust
sakex/neat-gru-rust - neat-gru
nerosnm/n2 - (Work-in-progress) library implementation of a feedforward, backpropagation artificial neural network
Wuelle/deep_thought - Neural Networks in Rust
MikhailKravets/NeuroFlow - Awesome deep learning crate
dvigneshwer/deeprust - Machine learning crate in Rust
millardjn/rusty_sr - Deep learning superresolution in pure rust


==Графовые модели==
==СТАТИСТИКА==
Synerise/cleora - Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.
* [https://github.com/statrs-dev/statrs statrs-dev/statrs - Statistical computation library for Rust]<br>
Pardoxa/net_ensembles - Rust library for random graph ensembles
* [https://github.com/rust-ndarray/ndarray-stats rust-ndarray/ndarray-stats - Statistical routines for ndarray]<br>
* [https://github.com/Axect/Peroxide Axect/Peroxide - Rust numeric library with R, MATLAB & Python syntaxLinear Algebra, Functional Programming, Automatic Differentiation, Numerical Analysis, Statistics, Special functions, Plotting, Dataframe]<br>
* [https://github.com/tarcieri/micromath tarcieri/micromath - Embedded Rust arithmetic, 2D/3D vector, and statistics library]<br>


==НЛП==
==ГРАДИЕНТНЫЙ БУСТИНГ(Gradient Boosting) ==
huggingface/tokenizers - The core of tokenizers, written in Rust. Provides an implementation of today's most used tokenizers, with a focus on performance and versatility.
* [https://github.com/mesalock-linux/gbdt-rs mesalock-linux/gbdt-rs - MesaTEE GBDT-RS : a fast and secure GBDT library, supporting TEEs such as Intel SGX and ARM TrustZone]<br>
guillaume-be/rust-tokenizers - Rust-tokenizer offers high-performance tokenizers for modern language models, including WordPiece, Byte-Pair Encoding (BPE) and Unigram (SentencePiece) models
* [https://github.com/davechallis/rust-xgboost davechallis/rust-xgboost - Rust bindings for XGBoost.]<br>
guillaume-be/rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
* [https://github.com/vaaaaanquish/lightgbm-rs vaaaaanquish/lightgbm-rs - LightGBM Rust binding]<br>
sno2/bertml - Use common pre-trained ML models in Deno!
* [https://github.com/catboost/catboost/tree/master/catboost/rust-package catboost/catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks (predict only)]<br>
cpcdoy/rust-sbert - Rust port of sentence-transformers (https://github.com/UKPLab/sentence-transformers)
* [https://github.com/entscheider/stamm Entscheider/stamm - Generic decision trees for rust]<br>
vongaisberg/gpt3_macro - Rust macro that uses GPT3 codex to generate code at compiletime
proycon/deepfrog - An NLP-suite powered by deep learning
ferristseng/rust-tfidf - Library to calculate TF-IDF
messense/fasttext-rs - fastText Rust binding
mklf/word2vec-rs - pure rust implementation of word2vec
DimaKudosh/word2vec - Rust interface to word2vec.
lloydmeta/sloword2vec-rs - A naive (read: slow) implementation of Word2Vec. Uses BLAS behind the scenes for speed.


==Рекомендательные системы==
==НЕЙРОННЫЕ СЕТИ==
PersiaML/PERSIA - High performance distributed framework for training deep learning recommendation models based on PyTorch.
* '''Tensorflow''' и '''PyTorch''' являются наиболее распространенными библиотеками для построения нейронных сетей.
jackgerrits/vowpalwabbit-rs - 🦀🐇 Rusty VowpalWabbit
outbrain/fwumious_wabbit - Fwumious Wabbit, fast on-line machine learning toolkit written in Rust
hja22/rucommender - Rust implementation of user-based collaborative filtering
maciejkula/sbr-rs - Deep recommender systems for Rust
chrisvittal/quackin - A recommender systems framework for Rust
snd/onmf - fast rust implementation of online nonnegative matrix factorization as laid out in the paper "detect and track latent factors with online nonnegative matrix factorization"
rhysnewell/nymph - Non-Negative Matrix Factorization in Rust


==Работа с текстом==
* [https://github.com/tensorflow/rusttensorflow/rust Rust language bindings for TensorFlow]<br>
quickwit-inc/quickwit - Quickwit is a big data search engine.
* [https://github.com/LaurentMazare/tch-rs LaurentMazare/tch-rs - Rust bindings for the C++ api of PyTorch.]<br>
bayard-search/bayard - A full-text search and indexing server written in Rust.
* [https://github.com/vasanthakumarv/einops VasanthakumarV/einops - Simplistic API for deep learning tensor operations]<br>
neuml/txtai.rs - AI-powered search engine for Rust
* [https://github.com/spearow/juice spearow/juice - The Hacker's Machine Learning Engine]<br>
meilisearch/MeiliSearch - Lightning Fast, Ultra Relevant, and Typo-Tolerant Search Engine
* [https://github.com/neuronika/neuronika neuronika/neuronika - Tensors and dynamic neural networks in pure Rust.]<br>
toshi-search/Toshi - A full-text search engine in rust
* [https://github.com/neuronika/neuronika bilal2vec/L2 - l2 is a fast, Pytorch-style Tensor+Autograd library written in Rust]<br>
BurntSushi/fst - Represent large sets and maps compactly with finite state transducers.
* [https://github.com/raskr/rust-autograd raskr/rust-autograd - Tensors and differentiable operations (like TensorFlow) in Rust]<br>
tantivy-search/tantivy - Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
* [https://github.com/charles-r-earp/autograph charles-r-earp/autograph - Machine Learning Library for Rust]<br>
tinysearch/tinysearch - 🔍 Tiny, full-text search engine for static websites built with Rust and Wasm
* [https://github.com/patricksongzy/corgi patricksongzy/corgi - A neural network, and tensor dynamic automatic differentiation implementation for Rust.]<br>
quantleaf/probly-search - A lightweight full-text search library that provides full control over the scoring calculations
* [https://github.com/JonathanWoollett-Light/cogent JonathanWoollett-Light/cogent - Simple neural network library for classification written in Rust.]<br>
https://github.com/andylokandy/simsearch-rs - A simple and lightweight fuzzy search engine that works in memory, searching for similar strings
* [https://github.com/oliverfunk/darknet-rs oliverfunk/darknet-rs - Rust bindings for darknet]<br>
jameslittle230/stork - 🔎 Impossibly fast web search, made for static sites.
* [https://github.com/jakelee8/mxnet-rs jakelee8/mxnet-rs - mxnet for Rust]<br>
elastic/elasticsearch-rs - Official Elasticsearch Rust Client
* [https://github.com/jramapuram/hal jramapuram/hal - Rust based Cross-GPU Machine Learning]<br>
* [https://github.com/primitiv/primitiv-rust primitiv/primitiv-rust - Rust binding of primitiv]<br>
* [https://github.com/chantera/dynet-rschantera/dynet-rs The Rust Language Bindings for DyNet]<br>
* [https://github.com/millardjn/alumina millardjn/alumina - A deep learning library for rust]<br>
* [https://github.com/jramapuram/hal jramapuram/hal - Rust based Cross-GPU Machine Learning]<br>
* [https://github.com/afck/fann-rs afck/fann-rs - Rust wrapper for the Fast Artificial Neural Network library]<br>
* [https://github.com/autumnai/leaf autumnai/leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU)]<br>
* [https://github.com/c0dearm/mushin c0dearm/mushin - Compile-time creation of neural networks]<br>
* [https://github.com/tedsta/deeplearn-rs tedsta/deeplearn-rs - Neural networks in Rust]<br>
* [https://github.com/sakex/neat-gru-rust sakex/neat-gru-rust - neat-gru]<br>
* [https://github.com/nerosnm/n2 nerosnm/n2 - (Work-in-progress) library implementation of a feedforward, backpropagation artificial neural network]<br>
* [https://github.com/Wuelle/deep_thought Wuelle/deep_thought - Neural Networks in Rust]<br>
* [https://github.com/MikhailKravets/NeuroFlow MikhailKravets/NeuroFlow - Awesome deep learning crate]<br>
* [https://github.com/dvigneshwer/deeprust dvigneshwer/deeprust - Machine learning crate in Rust]<br>
* [https://github.com/millardjn/rusty_sr millardjn/rusty_sr - Deep learning superresolution in pure rust]<br>


==Алгоритмы поиска ближайших соседей.==
==ГРАФОВЫЕ МОДЕЛИ==
Enet4/faiss-rs - Rust language bindings for Faiss
* [https://github.com/Synerise/cleora Synerise/cleora Cleora AI is a general-purpose model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data.]<br>
rust-cv/hnsw - HNSW ANN from the paper "Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs"
* [https://github.com/Pardoxa/net_ensemblesPardoxa/net_ensembles Rust library for random graph ensembles]<br>
hora-search/hora - 🚀 efficient approximate nearest neighbor search algorithm collections library, which implemented with Rust 🦀. horasearch.com
InstantDomain/instant-distance - Fast approximate nearest neighbor searching in Rust, based on HNSW index
lerouxrgd/ngt-rs - Rust wrappers for NGT approximate nearest neighbor search
granne/granne - Graph-based Approximate Nearest Neighbor Search
u1roh/kd-tree - k-dimensional tree in Rust. Fast, simple, and easy to use.
qdrant/qdrant - Qdrant - vector similarity search engine with extended filtering support
rust-cv/hwt - Hamming Weight Tree from the paper "Online Nearest Neighbor Search in Hamming Space"
fulara/kdtree-rust - kdtree implementation for rust.
mrhooray/kdtree-rs - K-dimensional tree in Rust for fast geospatial indexing and lookup
kornelski/vpsearch - C library for finding nearest (most similar) element in a set
petabi/petal-neighbors - Nearest neighbor search algorithms including a ball tree and a vantage point tree.
ritchie46/lsh-rs - Locality Sensitive Hashing in Rust with Python bindings
kampersanda/mih-rs - Rust implementation of multi-index hashing for neighbor searches on 64-bit codes in the Hamming space


==Обучение с подкреплением==
==НЕЙРОЛИНГВИСТИЧЕСКОЕ ПРОГРАММИРОВАНИЕ==
taku-y/border - Border is a reinforcement learning library in Rust.
* [https://github.com/huggingface/tokenizers/tree/master/tokenizers huggingface/tokenizers - The core of tokenizers, written in Rust. Provides an implementation of today's most used tokenizers, with a focus on performance and versatility.]<br>
NivenT/REnforce - Reinforcement learning library written in Rust
* [https://github.com/guillaume-be/rust-tokenizers guillaume-be/rust-tokenizers - Rust-tokenizer offers high-performance tokenizers for modern language models, including WordPiece, Byte-Pair Encoding (BPE) and Unigram (SentencePiece) models]<br>
edlanglois/relearn - Reinforcement learning with Rust
* [https://github.com/guillaume-be/rust-bert guillaume-be/rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)]
tspooner/rsrl - A fast, safe and easy to use reinforcement learning framework in Rust.
* [https://github.com/sno2/bertml sno2/bertml - Use common pre-trained ML models in Deno!]<br>
milanboers/rurel - Flexible, reusable reinforcement learning (Q learning) implementation in Rust
* [https://github.com/cpcdoy/rust-sbert cpcdoy/rust-sbert]<br>
Ragnaroek/bandit - Bandit Algorithms in Rust
* [https://github.com/UKPLab/sentence-transformers Rust port of sentence-transformers]<br>
MrRobb/gym-rs - OpenAI Gym bindings for Rust
* [https://github.com/vongaisberg/gpt3_macro vongaisberg/gpt3_macro - Rust macro that uses GPT3 codex to generate code at compiletime]<br>
* [https://github.com/proycon/deepfrog proycon/deepfrog - An NLP-suite powered by deep learning]<br>
* [https://github.com/ferristseng/rust-tfidf ferristseng/rust-tfidf - Library to calculate TF-IDF]<br>
* [https://github.com/messense/fasttext-rs messense/fasttext-rs - fastText Rust binding]<br>
* [https://github.com/mklf/word2vec-rs mklf/word2vec-rs - pure rust implementation of word2vec]<br>
* [https://github.com/DimaKudosh/word2vec DimaKudosh/word2vec - Rust interface to word2vec.]<br>
* [https://github.com/lloydmeta/sloword2vec-rs lloydmeta/sloword2vec-rs - A naive (read: slow) implementation of Word2Vec. Uses BLAS behind the scenes for speed.]<br>


==Обучение с учителем==
==РЕКОМЕНДАТЕЛЬНЫЕ СИСТЕМЫ==
tomtung/omikuji - An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification
* [https://github.com/PersiaML/PERSIA PersiaML/PERSIA - High performance distributed framework for training deep learning recommendation models based on PyTorch.]<br>
shadeMe/liblinear-rs - Rust language bindings for the LIBLINEAR C/C++ library.
* [https://github.com/jackgerrits/vowpalwabbit-rs jackgerrits/vowpalwabbit-rs Rusty VowpalWabbit]<br>
messense/crfsuite-rs - Rust binding to crfsuite
* [https://github.com/outbrain/fwumious_wabbit outbrain/fwumious_wabbit - Fwumious Wabbit, fast on-line machine learning toolkit written in Rust]<br>
ralfbiedert/ffsvm-rust - FFSVM stands for "Really Fast Support Vector Machine"
* [https://github.com/hja22/rucommender hja22/rucommender - Rust implementation of user-based collaborative filtering]<br>
zenoxygen/bayespam - A simple bayesian spam classifier written in Rust.
* [https://github.com/maciejkula/sbr-rs maciejkula/sbr-rs - Deep recommender systems for Rust]<br>
Rui_Vieira/naive-bayesnaive-bayes - A Naive Bayes classifier written in Rust.
* [https://github.com/chrisvittal/quackin chrisvittal/quackin - A recommender systems framework for Rust]<br>
Rui_Vieira/random-forests - A Rust library for Random Forests.
* [https://github.com/snd/onmf snd/onmf - fast rust implementation of online nonnegative matrix factorization as laid out in the paper "detect and track latent factors with online nonnegative matrix factorization"]<br>
sile/randomforest - A random forest implementation in Rust
* [https://github.com/rhysnewell/nymph rhysnewell/nymph - Non-Negative Matrix Factorization in Rust]<br>
tomtung/craftml-rs - A Rust🦀 implementation of CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning
nkaush/naive-bayes-rs - A Rust library with homemade machine learning models to classify the MNIST dataset. Built in an attempt to get familiar with advanced Rust concepts.


==Обучение без учителя==
==РАБОТА С ТЕКСТОМ==
frjnn/bhtsne - Barnes-Hut t-SNE implementation written in Rust.
* [https://github.com/quickwit-inc/quickwitquickwit-inc/quickwit Quickwit is a big data search engine.]<br>
vaaaaanquish/label-propagation-rs - Label Propagation Algorithm by Rust. Label propagation (LP) is graph-based semi-supervised learning (SSL). LGC and CAMLP have been implemented.
* [https://github.com/bayard-search/bayard bayard-search/bayard Full-text search and indexing server written in Rust.]<br>
nmandery/extended-isolation-forest - Rust port of the extended isolation forest algorithm for anomaly detection
* [https://github.com/neuml/txtai.rs neuml/txtai.rs AI-powered search engine for Rust]<br>
avinashshenoy97/RusticSOM - Rust library for Self Organising Maps (SOM).
* [https://github.com/meilisearch/MeiliSearch meilisearch/MeiliSearch - Lightning Fast, Ultra Relevant, and Typo-Tolerant Search Engine]<br>
diffeo/kodama - Fast hierarchical agglomerative clustering in Rust.
* [https://github.com/toshi-search/Toshi toshi-search/Toshi Full-text search engine in rust]<br>
kno10/rust-kmedoids - k-Medoids clustering in Rust with the FasterPAM algorithm
* [https://github.com/BurntSushi/fst BurntSushi/fst Represent large sets and maps compactly with finite state transducers.]<br>
petabi/petal-clustering - DBSCAN and OPTICS clustering algorithms.
* [https://github.com/tantivy-search/tantivy tantivy-search/tantivy Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust]<br>
savish/dbscan - A naive DBSCAN implementation in Rust
* [https://github.com/tinysearch/tinysearch tinysearch/tinysearch  🔍 Tiny, full-text search engine for static websites built with Rust and Wasm]<br>
gu18168/DBSCANSD - Rust implementation for DBSCANSD, a trajectory clustering algorithm.
* [https://github.com/quantleaf/probly-search quantleaf/probly-search Lightweight full-text search library that provides full control over the scoring calculations]<br>
lazear/dbscan - Dependency free implementation of DBSCAN clustering in Rust
* [https://github.com/andylokandy/simsearch-rs Simple and lightweight fuzzy search engine that works in memory, searching for similar strings]<br>
whizsid/kddbscan-rs - A rust library inspired by kDDBSCAN clustering algorithm
* [https://github.com/jameslittle230/stork jameslittle230/stork Impossibly fast web search, made for static sites.]<br>
Sauro98/appr_dbscan_rust - Program implementing the approximate version of DBSCAN introduced by Gan and Tao
* [https://github.com/elastic/elasticsearch-rs elastic/elasticsearch-rs - Official Elasticsearch Rust Client]<br>
quietlychris/density_clusters - A naive density-based clustering algorithm written in Rust
milesgranger/gap_statistic - Dynamically get the suggested clusters in the data for unsupervised learning.
genbattle/rkm - Generic k-means implementation written in Rust
selforgmap/som-rust - Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.


==Статистические модели==
==АЛГОРИТМЫ ПОИСКА БЛИЖАЙШИХ СОСЕДЕЙ==
Redpoll/changepoint - Includes the following change point detection algorithms: Bocpd -- Online Bayesian Change Point Detection Reference. BocpdTruncated -- Same as Bocpd but truncated the run-length distribution when those lengths are unlikely.
* [https://github.com/Enet4/faiss-rs Enet4/faiss-rs - Rust language bindings for Faiss]<br>
krfricke/arima - ARIMA modelling for Rust
* [https://github.com/rust-cv/hnsw rust-cv/hnsw - HNSW ANN from the paper "Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs"]<br>
Daingun/automatica - Automatic Control Systems Library
* [https://github.com/hora-search/hora hora-search/hora Efficient approximate nearest neighbor search algorithm collections library, which implemented with Rust. horasearch.com]<br>
rbagd/rust-linearkalman - Kalman filtering and smoothing in Rust
* [https://github.com/InstantDomain/instant-distance InstantDomain/instant-distance - Fast approximate nearest neighbor searching in Rust, based on HNSW index]<br>
sanity/pair_adjacent_violators - An implementation of the Pair Adjacent Violators algorithm for isotonic regression in Rust
* [https://github.com/lerouxrgd/ngt-rs lerouxrgd/ngt-rs - Rust wrappers for NGT approximate nearest neighbor search]<br>
* [https://github.com/granne/granne granne/granne - Graph-based Approximate Nearest Neighbor Search]<br>
* [https://github.com/u1roh/kd-tree u1roh/kd-tree - k-dimensional tree in Rust. Fast, simple, and easy to use.]<br>
* [https://github.com/qdrant/qdrant qdrant/qdrant - Qdrant - vector similarity search engine with extended filtering support]<br>
* [https://github.com/rust-cv/hwt rust-cv/hwt - Hamming Weight Tree from the paper "Online Nearest Neighbor Search in Hamming Space"]<br>
* [https://github.com/fulara/kdtree-rust fulara/kdtree-rust - kdtree implementation for rust.]<br>
* [https://github.com/mrhooray/kdtree-rs mrhooray/kdtree-rs - K-dimensional tree in Rust for fast geospatial indexing and lookup]<br>
* [https://github.com/kornelski/vpsearch kornelski/vpsearch - C library for finding nearest (most similar) element in a set]<br>
* [https://github.com/petabi/petal-neighbors petabi/petal-neighbors - Nearest neighbor search algorithms including a ball tree and a vantage point tree.]<br>
* [https://github.com/ritchie46/lsh-rs ritchie46/lsh-rs - Locality Sensitive Hashing in Rust with Python bindings]<br>
* [https://github.com/kampersanda/mih-rs kampersanda/mih-rs - Rust implementation of multi-index hashing for neighbor searches on 64-bit codes in the Hamming space]<br>


==Эволюционные алгоритмы==
==ОБУЧЕНИЕ С ПОДКРЕПЛЕНИЕМ==
martinus/differential-evolution-rs - Generic Differential Evolution for Rust
* [https://github.com/taku-y/border taku-y/border Border is a reinforcement learning library in Rust]<br>
innoave/genevo - Execute genetic algorithm (GA) simulations in a customizable and extensible way.
* [https://github.com/NivenT/REnforce NivenT/REnforce Reinforcement learning library written in Rust]<br>
Jeffail/spiril - Rust library for genetic algorithms
* [https://github.com/edlanglois/relearn edlanglois/relearn Reinforcement learning with Rust]<br>
sotrh/rust-genetic-algorithm - Example of a genetic algorithm in Rust and Python
* [https://github.com/tspooner/rsrl tspooner/rsrl Fast, safe and easy to use reinforcement learning framework in Rust.]<br>
willi-kappler/darwin-rs - darwin-rs, evolutionary algorithms with rust
* [https://github.com/milanboers/rurel milanboers/rurel Flexible, reusable reinforcement learning (Q learning) implementation in Rust]<br>
* [https://github.com/Ragnaroek/banditRagnaroek/bandit Bandit Algorithms in Rust]<br>
* [https://github.com/mrrobb/gym-rs MrRobb/gym-rs - OpenAI Gym bindings for Rust]<br>


==Еще проекты==
==ОБУЧЕНИЕ С УЧИТЕЛЕМ==
Are we learning yet?, A work-in-progress to catalog the state of machine learning in Rust
* [https://github.com/tomtung/omikuji tomtung/omikuji - An efficient implementation of Partitioned Label Trees & its variations for extreme multi-label classification] <br>
e-tony/best-of-ml-rust, A ranked list of awesome machine learning Rust libraries
* [https://github.com/shademe/liblinear-rs shadeMe/liblinear-rs - Rust language bindings for the LIBLINEAR C/C++ library.]<br>
The Best 51 Rust Machine learning Libraries, RustRepo
* [https://github.com/messense/crfsuite-rs messense/crfsuite-rs - Rust binding to crfsuite]<br>
rust-unofficial/awesome-rust, A curated list of Rust code and resources
* [https://github.com/ralfbiedert/ffsvm-rust ralfbiedert/ffsvm-rust - FFSVM stands for "Really Fast Support Vector Machine"]<br>
Top 16 Rust Machine learning Projects, Open-source Rust projects categorized as Machine learning
* [https://github.com/zenoxygen/bayespam zenoxygen/bayespam - A simple bayesian spam classifier written in Rust.]<br>
39+ Best Rust Machine learning frameworks, libraries, software and resourcese, ReposHub
* [https://gitlab.com/ruivieira/naive-bayes Rui_Vieira/naive-bayesnaive-bayes - A Naive Bayes classifier written in Rust.]<br>
* [https://gitlab.com/ruivieira/random-forests Rui_Vieira/random-forests - A Rust library for Random Forests.]<br>
* [https://github.com/sile/randomforest sile/randomforest - A random forest implementation in Rust]<br>
* [https://github.com/tomtung/craftml-rs tomtung/craftml-rs - A Rust🦀 implementation of CRAFTML, an Efficient Clustering-based Random Forest for Extreme Multi-label Learning]<br>
* [https://github.com/nkaush/naive-bayes-rs nkaush/naive-bayes-rs - A Rust library with homemade machine learning models to classify the MNIST dataset. Built in an attempt to get familiar with advanced Rust concepts.]<br>


==Блоги==
==ОБУЧЕНИЕ БЕЗ УЧИТЕЛЯ==
About Rust’s Machine Learning Community, Medium, 2016/1/6, Autumn Engineering
* [https://github.com/frjnn/bhtsne frjnn/bhtsne - Barnes-Hut t-SNE implementation written in Rust.]<br>
Rust vs Python: Technology And Business Comparison, 2021/3/4, Miłosz Kaczorowski
* [https://github.com/vaaaaanquish/label-propagation-rs vaaaaanquish/label-propagation-rs - Label Propagation Algorithm by Rust. Label propagation (LP) is graph-based semi-supervised learning (SSL). LGC and CAMLP have been implemented.]<br>
I wrote one of the fastest DataFrame libraries, 2021/2/28, Ritchie Vink
* [https://github.com/nmandery/extended-isolation-forest nmandery/extended-isolation-forest - Rust port of the extended isolation forest algorithm for anomaly detection]<br>
Polars: The fastest DataFrame library you've never heard of 2021/1/19, Analytics Vidhya
* [https://github.com/avinashshenoy97/RusticSOM avinashshenoy97/RusticSOM - Rust library for Self Organising Maps (SOM).]<br>
Data Manipulation: Polars vs Rust, 2021/3/13, Xavier Tao
* [https://github.com/diffeo/kodama diffeo/kodama - Fast hierarchical agglomerative clustering in Rust.]<br>
State of Machine Learning in Rust – Ehsan's Blog, 2019/5/13, Published by Ehsan
* [https://github.com/kno10/rust-kmedoids kno10/rust-kmedoids - k-Medoids clustering in Rust with the FasterPAM algorithm]<br>
Ritchie Vink, Machine Learning Engineer, writes Polars, one of the fastest DataFrame libraries in Python and Rust, Xomnia, 2021/5/11
* [https://github.com/petabi/petal-clustering petabi/petal-clustering - DBSCAN and OPTICS clustering algorithms.]<br>
Quickwit: A highly cost-efficient search engine in Rust, 2021/7/13, quickwit, PAUL MASUREL
* [https://github.com/savish/dbscan savish/dbscan - A naive DBSCAN implementation in Rust]<br>
Data Manipulation: Polars vs Rust, 2021/3/13, Xavier Tao
* [https://github.com/gu18168/DBSCANSD gu18168/DBSCANSD - Rust implementation for DBSCANSD, a trajectory clustering algorithm.]<br>
Check out Rust in Production, 2021/8/10, Qovery, @serokell
* [https://github.com/lazear/dbscan lazear/dbscan - Dependency free implementation of DBSCAN clustering in Rust]<br>
Why I started Rust instead of stick to Python, 2021/9/26, Medium, Geek Culture, Marshal SHI
* [https://github.com/whizsid/kddbscan-rs whizsid/kddbscan-rs - A rust library inspired by kDDBSCAN clustering algorithm]<br>
* [https://github.com/Sauro98/appr_dbscan_rust Sauro98/appr_dbscan_rust - Program implementing the approximate version of DBSCAN introduced by Gan and Tao]<br>
* [https://github.com/quietlychris/density_clusters quietlychris/density_clusters - A naive density-based clustering algorithm written in Rust]<br>
* [https://github.com/milesgranger/gap_statistic milesgranger/gap_statistic - Dynamically get the suggested clusters in the data for unsupervised learning.]<br>
* [https://github.com/genbattle/rkm genbattle/rkm - Generic k-means implementation written in Rust]<br>
* [https://github.com/selforgmap/som-rust selforgmap/som-rust - Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.]<br>


==Обучения==
==СТАТИСТИЧЕСКИЕ МОДЕЛИ==
Rust Machine Learning Book, Examples of KMeans and DBSCAN with linfa-clustering
* [https://gitlab.com/Redpoll/changepoint Redpoll/changepoint - Includes the following change point detection algorithms: Bocpd -- Online Bayesian Change Point Detection Reference. BocpdTruncated -- Same as Bocpd but truncated the run-length distribution when those lengths are unlikely.]<br>
Artificial Intelligence and Machine Learning – Practical Rust Projects: Building Game, Physical Computing, and Machine Learning Applications – Dev Guis , 2021/5/19
* [https://github.com/krfricke/arima krfricke/arima - ARIMA modelling for Rust]<br>
Machine learning in Rust using Linfa, LogRocket Blog, 2021/4/30, Timeular, Mario Zupan, Examples of LogisticRegression
* [https://gitlab.com/daingun/automatica Daingun/automatica - Automatic Control Systems Library]<br>
Machine Learning in Rust, Smartcore, Medium, The Startup, 2021/1/15, Vlad Orlov, Examples of LinerRegression, Random Forest Regressor, and K-Fold
* [https://github.com/rbagd/rust-linearkalman rbagd/rust-linearkalman - Kalman filtering and smoothing in Rust]<br>
Machine Learning in Rust, Logistic Regression, Medium, The Startup, 2021/1/6, Vlad Orlov
* [https://github.com/sanity/pair_adjacent_violators sanity/pair_adjacent_violators - An implementation of the Pair Adjacent Violators algorithm for isotonic regression in Rust]<br>
Machine Learning in Rust, Linear Regression, Medium, The Startup, 2020/12/16, Vlad Orlov
Machine Learning in Rust, 2016/3/7, James, Examples of LogisticRegressor
Machine Learning and Rust (Part 1): Getting Started!, Level Up Coding, 2021/1/9, Stefano Bosisio
Machine Learning and Rust (Part 2): Linear Regression, Level Up Coding, 2021/6/15, Stefano Bosisio
Machine Learning and Rust (Part 3): Smartcore, Dataframe, and Linear Regression, Level Up Coding, 2021/7/1, Stefano Bosisio
Tensorflow Rust Practical Part 1, Programmer Sought, 2018
A Machine Learning introduction to ndarray, RustFest 2019, 2019/11/12, Luca Palmieri
Simple Linear Regression from scratch in Rust, Web Development, Software Architecture, Algorithms and more, 2018/12/13, philipp
Interactive Rust in a REPL and Jupyter Notebook with EVCXR, Depth-First, 2020/9/21, Richard L. Apodaca
Rust for Data Science: Tutorial 1, dev, 2021/8/25, Davide Del Papa
petgraph_review, 2019/10/11, Timothy Hobbs
Rust for ML. Rust, Medium, Tempus Ex, 2021/8/1, Michael Naquin
Adventures in Drone Photogrammetry Using Rust and Machine Learning (Image Segmentation with linfa and DBSCAN), 2021/11/14, CHRISTOPHER MORAN


==Прикладные ресурсы==
==ЭВОЛЮЦИОННЫЕ АЛГОРИТМЫ==
Deep Learning in Rust: baby steps, Medium, 2016/2/2, Theodore DeRego
* [https://github.com/martinus/differential-evolution-rs martinus/differential-evolution-rs - Generic Differential Evolution for Rust]<br>
A Rust SentencePiece implementation, Rust NLP tales, 2020/5/30
* [https://github.com/innoave/genevo innoave/genevo - Execute genetic algorithm (GA) simulations in a customizable and extensible way.]<br>
Accelerating text generation with Rust, Rust NLP tales, 2020/11/21
* [https://github.com/Jeffail/spiril Jeffail/spiril - Rust library for genetic algorithms]<br>
A Simple Text Summarizer written in Rust, Towards Data Science, 2020/11/24, Charles Chan, Examples of Text Sentence Vector, Cosine Distance and PageRank
* [https://github.com/sotrh/rust-genetic-algorithm sotrh/rust-genetic-algorithm - Example of a genetic algorithm in Rust and Python]<br>
Extracting deep learning image embeddings in Rust, RecoAI, 2021/6/1, Paweł Jankiewic, Examples of ONNX
* [https://github.com/willi-kappler/darwin-rs willi-kappler/darwin-rs - darwin-rs, evolutionary algorithms with Rust]<br>
Deep Learning in Rust with GPU, 2021/7/30, Xavier Tao
tch-rs pretrain example - Docker for PyTorch rust bindings tch-rs. Example of pretrain model, 2021/8/15, vaaaaanquish
Rust ANN search Example - Image search example by approximate nearest-neighbor library In Rust, 2021/8/15, vaaaaanquish
dzamkov/deep-learning-test - Implementing deep learning in Rust using just a linear algebra library (nalgebra), 2021/8/30, dzamkov
vaaaaanquish/rust-machine-learning-api-example - The axum example that uses resnet224 to infer images received in base64 and returns the results., 2021/9/7, vaaaaanquish
Rust for Machine Learning: Benchmarking Performance in One-shot - A Rust implementation of Siamese Neural Networks for One-shot Image Recognition for benchmarking performance and results, UofT Machine Intelligence Student Team
Why Wallaroo Moved From Pony To Rust, 2021/8/19, Wallaroo.ai
epwalsh/rust-dl-webserver - Example of serving deep learning models in Rust with batched prediction, 2021/11/16, epwalsh
Production users - Rust Programming Language, by rust-lang.org
Taking ML to production with Rust: a 25x speedup, A LEARNING JOURNAL, 2019/12/1, @algo_luca
9 Companies That Use Rust in Production, serokell, 2020/11/18, Gints Dreimanis
Masked Language Model on Wasm, BERT on flontend examples, optim-corp/masked-lm-wasm, 2021/8/27, Optim
Serving TensorFlow with Actix-Web, kykosic/actix-tensorflow-example
Serving PyTorch with Actix-Web, kykosic/actix-pytorch-example


==Форумы==
==ДРУГИЕ ПРОЕКТЫ==
Natural Language Processing in Rust : rust, 2016/12/6
* [http://www.arewelearningyet.com/ Are we learning yet?, A work-in-progress to catalog the state of machine learning in Rust]<br>
Future prospect of Machine Learning in Rust Programming Language : MachineLearning, 2017/11/11
* [https://github.com/e-tony/best-of-ml-rust e-tony/best-of-ml-rust, A ranked list of awesome machine learning Rust libraries]<br>
Interest for NLP in Rust? - The Rust Programming Language Forum, 2018/1/19
* [https://rustrepo.com/catalog/rust-machine-learning_newest_1 The Best 51 Rust Machine learning Libraries, RustRepo]<br>
Is Rust good for deep learning and artificial intelligence? - The Rust Programming Language Forum, 2018/11/18
* [https://github.com/rust-unofficial/awesome-rust rust-unofficial/awesome-rust, A curated list of Rust code and resources]<br>
ndarray vs nalgebra : rust, 2019/5/28
* [https://www.libhunt.com/l/rust/t/machine-learning Top 16 Rust Machine learning Projects, Open-source Rust projects categorized as Machine learning]<br>
Taking ML to production with Rust | Hacker News, 2019/12/2
* [https://reposhub.com/rust/machine-learning 39+ Best Rust Machine learning frameworks, libraries, software and resourcese, ReposHub]<br>
Who is using Rust for Machine learning in production/research? : rust, 2020/4/5
Deep Learning in Rust, 2020/8/26
SmartCore, fast and comprehensive machine learning library for Rust! : rust, 2020/9/29
Deep Learning in Rust with GPU on ONNX, 2021/7/31
Rust vs. C++ the main differences between these popular programming languages, 2021/8/25
I wanted to share my experience of Rust as a deep learning researcher, 2021/9/2
How far along is the ML ecosystem with Rust?, 2021/9/15


==Книги==
==БЛОГИ==
Practical Machine Learning with Rust: Creating Intelligent Applications in Rust (English Edition), 2019/12/10, Joydeep BhattacharjeeWrite machine learning algorithms in Rust
* [https://medium.com/@autumn_eng/about-rust-s-machine-learning-community-4cda5ec8a790#.hvkp56j3f About Rust’s Machine Learning Community, Medium, 2016/1/6, Autumn Engineering]<br>
Use Rust libraries for different tasks in machine learning
* [https://www.ideamotive.co/blog/rust-vs-python-technology-and-business-comparison Rust vs Python: Technology And Business Comparison, 2021/3/4, Miłosz Kaczorowski]<br>
Create concise Rust packages for your machine learning applications
* [https://www.ritchievink.com/blog/2021/02/28/i-wrote-one-of-the-fastest-dataframe-libraries I wrote one of the fastest DataFrame libraries, 2021/2/28, Ritchie Vink]<br>
Implement NLP and computer vision in Rust
* [https://www.analyticsvidhya.com/blog/2021/06/polars-the-fastest-dataframe-library-youve-never-heard-of Polars: The fastest DataFrame library you've never heard of 2021/1/19, Analytics Vidhya]<br>
Deploy your code in the cloud and on bare metal servers
* [https://able.bio/haixuanTao/data-manipulation-polars-vs-rust--3def44c8 Data Manipulation: Polars vs Rust, 2021/3/13, Xavier Tao]<br>
source code: Apress/practical-machine-learning-w-rust
* [https://ehsanmkermani.com/2019/05/13/state-of-machine-learning-in-rust/ State of Machine Learning in Rust – Ehsan's Blog, 2019/5/13, Published by Ehsan]<br>
DATA ANALYSIS WITH RUST NOTEBOOKS, 2021/9/3, Shahin RostamiPlotting with Plotters and Plotly
* [https://www.xomnia.com/post/ritchie-vink-writes-polars-one-of-the-fastest-dataframe-libraries-in-python-and-rust/ Ritchie Vink, Machine Learning Engineer, writes Polars, one of the fastest DataFrame libraries in Python and Rust, Xomnia, 2021/5/11]<br>
Operations with ndarray
* [https://quickwit.io/blog/quickwit-first-release/ Quickwit: A highly cost-efficient search engine in Rust, 2021/7/13, quickwit, PAUL MASUREL]<br>
Descriptive Statistics
* [https://serokell.io/blog/rust-in-production-qovery Check out Rust in Production, 2021/8/10, Qovery, @serokell]<br>
Interactive Diagram
* [https://medium.com/geekculture/why-i-started-rust-instead-of-stick-to-python-626bab07479a Why I started Rust instead of stick to Python, 2021/9/26, Medium, Geek Culture, Marshal SHI]<br>
Visualisation of Co-occurring Types
download source code and dataset


full texthttps://datacrayon.com/posts/programming/rust-notebooks/preface/
==ОБУЧЕНИЕ==
* [https://rust-ml.github.io/book/chapter_1.html Rust Machine Learning Book, Examples of KMeans and DBSCAN with linfa-clustering]<br>
* [http://devguis.com/6-artificial-intelligence-and-machine-learning-practical-rust-projects-building-game-physical-computing-and-machine-learning-applications.html Artificial Intelligence and Machine Learning – Practical Rust Projects(Building Game, Physical Computing) – Dev Guis , 2021/5/19]<br>
* [https://blog.logrocket.com/machine-learning-in-rust-using-linfa/ Machine learning in Rust using Linfa, LogRocket Blog, 2021/4/30, Timeular, Mario Zupan, Examples of LogisticRegression]<br>
* [https://medium.com/swlh/machine-learning-in-rust-smartcore-2f472d1ce83 Machine Learning in Rust, Smartcore, Medium, The Startup, 2021/1/15] (c) [https://volodymyr-orlov.medium.com/ Vlad Orlov]<br>
* [https://medium.com/swlh/machine-learning-in-rust-logistic-regression-74d6743df161 Machine Learning in Rust, Logistic Regression, Medium, The Startup, 2021/1/6] (c) [https://volodymyr-orlov.medium.com/ Vlad Orlov]<br>
* [https://medium.com/swlh/machine-learning-in-rust-linear-regression-edef3fb65f93 Machine Learning in Rust, Linear Regression, Medium, The Startup, 2020/12/16] (c) [https://volodymyr-orlov.medium.com/ Vlad Orlov]<br>
* [https://athemathmo.github.io/2016/03/07/rusty-machine.html Machine Learning in Rust, 2016/3/7, James, Examples of LogisticRegressor]<br>
* [https://levelup.gitconnected.com/machine-learning-and-rust-part-1-getting-started-745885771bc2 Machine Learning and Rust (Part 1): Getting Started!, Level Up Coding, 2021/1/9, Stefano Bosisio]<br>
* [https://levelup.gitconnected.com/machine-learning-and-rust-part-2-linear-regression-d3b820ed28f9 Machine Learning and Rust (Part 2): Linear Regression, Level Up Coding, 2021/6/15, Stefano Bosisio]<br>
* [https://levelup.gitconnected.com/machine-learning-and-rust-part-3-smartcore-dataframe-and-linear-regression-10451fdc2e60 Machine Learning and Rust (Part 3): Smartcore, Dataframe, and Linear Regression, Level Up Coding, 2021/7/1, Stefano Bosisio]<br>
* [https://www.programmersought.com/article/18696273900/ Tensorflow Rust Practical Part 1, Programmer Sought, 2018]<br>
* [https://barcelona.rustfest.eu/sessions/machine-learning-ndarray A Machine Learning introduction to ndarray, RustFest 2019, 2019/11/12] (c) [https://github.com/LukeMathWalker Luca Palmieri]<br>
* [https://cheesyprogrammer.com/2018/12/13/simple-linear-regression-from-scratch-in-rust/ Simple Linear Regression from scratch in Rust, Web Development, Software Architecture, Algorithms and more, 2018/12/13, philipp]<br>
* [https://depth-first.com/articles/2020/09/21/interactive-rust-in-a-repl-and-jupyter-notebook-with-evcxr/ Interactive Rust in a REPL and Jupyter Notebook with EVCXR, Depth-First, 2020/9/21, Richard L. Apodaca]<br>
* [https://dev.to/davidedelpapa/rust-for-data-science-tutorial-1-4g5j Rust for Data Science: Tutorial 1, dev, 2021/8/25, Davide Del Papa]<br>
* [https://timothy.hobbs.cz/rust-play/petgraph_review.html petgraph_review, 2019/10/11, Timothy Hobbs]<br>
* [https://medium.com/tempus-ex/rust-for-ml-fba0421b0959 Rust for ML. Rust, Medium, Tempus Ex, 2021/8/1, Michael Naquin]<br>
* [http://cmoran.xyz/writing/adventures_in_photogrammetry Adventures in Drone Photogrammetry Using Rust and Machine Learning (Image Segmentation with linfa and DBSCAN), 2021/11/14, CHRISTOPHER MORAN]<br>


==Видео уроки==
==ПРИКЛАДНЫЕ РЕСУРСЫ==
The /r/playrust Classifier: Real World Rust Data Science, RustConf 2016, 2016/10/05, Suchin Gururangan & Colin O'Brien
* [https://medium.com/@tedsta/deep-learning-in-rust-7e228107cccc Deep Learning in Rust: baby steps, Medium, 2016/2/2, Theodore DeRego]<br>
Building AI Units in Rust, FOSSASIA 2018, 2018/3/25, Vigneshwer Dhinakaran
* [https://guillaume-be.github.io/2020-05-30/sentence_piece A Rust SentencePiece implementation, Rust NLP tales, 2020/5/30]<br>
Python vs Rust for Simulation, EuroPython 2019, 2019/7/10, Alisa Dammer
* [https://guillaume-be.github.io/2020-11-21/generation_benchmarks Accelerating text generation with Rust, Rust NLP tales, 2020/11/21]<br>
Machine Learning is changing - is Rust the right tool for the job?, RustLab 2019, 2019/10/31, Luca Palmieri
* [https://towardsdatascience.com/a-simple-text-summarizer-written-in-rust-4df05f9327a5 A Simple Text Summarizer written in Rust, Towards Data Science, 2020/11/24,Examples of Text Sentence Vector, Cosine Distance and PageRank] (c)[https://chancharles.medium.com/ Charles Chan]<br>
Using TensorFlow in Embedded Rust, 2020/09/29, Ferrous Systems GmbH, Richard Meadows
* [https://logicai.io/blog/extracting-image-embeddings/ Extracting deep learning image embeddings in Rust, RecoAI, 2021/6/1, Paweł Jankiewic, Examples of ONNX]<br>
Writing the Fastest GBDT Library in Rust, 2021/09/16, RustConf 2021, Isabella Tromba
* [https://able.bio/haixuanTao/deep-learning-in-rust-with-gpu--26c53a7f Deep Learning in Rust with GPU, 2021/7/30, Xavier Tao]<br>
* [https://github.com/vaaaaanquish/tch-rs-pretrain-example-docker tch-rs pretrain example - Docker for PyTorch rust bindings tch-rs. Example of pretrain model, 2021/8/15, vaaaaanquish]<br>
* [https://github.com/vaaaaanquish/rust-ann-search-example Rust ANN search Example - Image search example by approximate nearest-neighbor library In Rust, 2021/8/15, vaaaaanquish]<br>
* [https://github.com/dzamkov/deep-learning-test dzamkov/deep-learning-test - Implementing deep learning in Rust using just a linear algebra library (nalgebra), 2021/8/30, dzamkov]<br>
* [https://github.com/vaaaaanquish/rust-machine-learning-api-example vaaaaanquish/rust-machine-learning-api-example - The axum example that uses resnet224 to infer images received in base64 and returns the results., 2021/9/7, vaaaaanquish]<br>
* [https://utmist.gitlab.io/projects/rust-ml-oneshot/ Rust for Machine Learning: Benchmarking Performance in One-shot - A Rust implementation of Siamese Neural Networks for One-shot Image Recognition for benchmarking performance and results, UofT Machine Intelligence Student Team]<br>
* [https://wallarooai.medium.com/why-wallaroo-moved-from-pony-to-rust-292e7339fc34 Why Wallaroo Moved From Pony To Rust, 2021/8/19, Wallaroo.ai]<br>
* [https://github.com/epwalsh/rust-dl-webserver epwalsh/rust-dl-webserver - Example of serving deep learning models in Rust with batched prediction, 2021/11/16, epwalsh]<br>
* [https://www.rust-lang.org/production/users Production users - Rust Programming Language, by rust-lang.org]<br>
* [https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/ Taking ML to production with Rust: a 25x speedup, A LEARNING JOURNAL, 2019/12/1] (c) [https://twitter.com/algo_luca @algo_luca]<br>
* [https://serokell.io/blog/rust-companies 9 Companies That Use Rust in Production, serokell, 2020/11/18, Gints Dreimanis]<br>
* [https://github.com/optim-corp/masked-lm-wasm/ Masked Language Model on Wasm, BERT on flontend examples, optim-corp/masked-lm-wasm, 2021/8/27, Optim]<br>
* [https://github.com/kykosic/actix-tensorflow-example Serving TensorFlow with Actix-Web, kykosic/actix-tensorflow-example]<br>
* [https://github.com/kykosic/actix-pytorch-example Serving PyTorch with Actix-Web, kykosic/actix-pytorch-example]<br>
 
==ФОРУМЫ==
* [https://www.reddit.com/r/rust/comments/5jj8vr/natural_language_processing_in_rust Natural Language Processing in Rust : rust, 2016/12/6]<br>
* [https://www.reddit.com/r/MachineLearning/comments/7iz51p/d_future_prospect_of_machine_learning_in_rust/ Future prospect of Machine Learning in Rust Programming Language : MachineLearning, 2017/11/11]<br>
* [https://users.rust-lang.org/t/interest-for-nlp-in-rust/15331 Interest for NLP in Rust? - The Rust Programming Language Forum, 2018/1/19]<br>
* [https://users.rust-lang.org/t/is-rust-good-for-deep-learning-and-artificial-intelligence/22866 Is Rust good for deep learning and artificial intelligence? - The Rust Programming Language Forum, 2018/11/18]<br>
* [https://www.reddit.com/r/rust/comments/btn1cz/ndarray_vs_nalgebra/ ndarray vs nalgebra : rust, 2019/5/28]<br>
* [https://news.ycombinator.com/item?id=21680965 Taking ML to production with Rust | Hacker News, 2019/12/2]<br>
* [https://www.reddit.com/r/rust/comments/fvehyq/d_who_is_using_rust_for_machine_learning_in/ Who is using Rust for Machine learning in production/research? : rust, 2020/4/5]<br>
* [https://www.reddit.com/r/rust/comments/igz8iv/deep_learning_in_rust/ Deep Learning in Rust, 2020/8/26]<br>
* [https://www.reddit.com/r/rust/comments/j1mj1g/smartcore_fast_and_comprehensive_machine_learning/ SmartCore, fast and comprehensive machine learning library for Rust! : rust, 2020/9/29]<br>
* [https://www.reddit.com/r/MachineLearning/comments/ouul33/d_p_deep_learning_in_rust_with_gpu_on_onnx/ Deep Learning in Rust with GPU on ONNX, 2021/7/31]<br>
* [https://codilime.com/blog/rust-vs-cpp-the-main-differences-between-these-popular-programming-languages/ Rust vs. C++ the main differences between these popular programming languages, 2021/8/25]<br>
* [https://www.reddit.com/r/rust/comments/pft9n9/i_wanted_to_share_my_experience_of_rust_as_a_deep/ I wanted to share my experience of Rust as a deep learning researcher, 2021/9/2]<br>
* [https://www.reddit.com/r/rust/comments/poglgg/how_far_along_is_the_ml_ecosystem_with_rust/ How far along is the ML ecosystem with Rust?, 2021/9/15]<br>
 
==КНИГИ==
* [https://amzn.to/3h7JV8U '''Practical Machine Learning with Rust: Creating Intelligent Applications in Rust (English Edition)''']<br>
-- 2019/12/10, Joydeep BhattacharjeeWrite machine learning algorithms in Rust<br>
- Use Rust libraries for different tasks in machine learning<br>
- Create concise Rust packages for your machine learning applications<br>
- Implement NLP and computer vision in Rust<br>
- Deploy your code in the cloud and on bare metal servers<br>
* [https://github.com/Apress/practical-machine-learning-w-rust source code for this Book]<br>
--
* [https://datacrayon.com/shop/product/data-analysis-with-rust-notebooks/ '''DATA ANALYSIS WITH RUST NOTEBOOKS''']<br>
-- 2021/9/3, Shahin RostamiPlotting with Plotters and Plotly<br>
- Operations with ndarray<br>
- Descriptive Statistics<br>
- Interactive Diagram<br>
- Visualisation of Co-occurring Types<br>
- download source code and dataset<br>
* [https://datacrayon.com/posts/programming/rust-notebooks/preface/ Full text book]<br>
 
==ВИДЕО УРОКИ==
* [https://www.youtube.com/watch?v=lY10kTcM8ek The /r/playrust Classifier: Real World Rust Data Science, RustConf 2016, 2016/10/05, Suchin Gururangan & Colin O'Brien]<br>
* [https://www.youtube.com/watch?v=UHFlKAmANJg Building AI Units in Rust, FOSSASIA 2018, 2018/3/25, Vigneshwer Dhinakaran]<br>
* [https://www.youtube.com/watch?v=kytvDxxedWY Python vs Rust for Simulation, EuroPython 2019, 2019/7/10, Alisa Dammer]<br>
* [https://www.youtube.com/watch?v=odI_LY8AIqo Machine Learning is changing - is Rust the right tool for the job?, RustLab 2019, 2019/10/31, Luca Palmieri]<br>
* [https://www.youtube.com/watch?v=DUVE86yTfKU Using TensorFlow in Embedded Rust, 2020/09/29, Ferrous Systems GmbH, Richard Meadows]<br>
* [https://www.youtube.com/watch?v=D1NAREuicNs Writing the Fastest GBDT Library in Rust, 2021/09/16, RustConf 2021, Isabella Tromba]<br>


==Подкасты==
==Подкасты==
DATA SCIENCE AT HOMERust and machine learning #1 (Ep. 107) Rust and machine learning #2 with Luca Palmieri (Ep. 108) Rust and machine learning #3 with Alec Mocatta (Ep. 109) Rust and machine learning #4: practical tools (Ep. 110) Machine Learning in Rust: Amadeus with Alec Mocatta (Ep. 127) Rust and deep learning with Daniel McKenna (Ep. 135) Is Rust flexible enough for a flexible data model? (Ep. 137) Pandas vs Rust (Ep. 144) Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145) Polars: the fastest dataframe crate in Rust (Ep. 146) Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)
DATA SCIENCE AT HOME:
* [https://datascienceathome.com/rust-and-machine-learning-1-ep-107/ Rust and machine learning #1 (Ep. 107)]<br>
* [https://datascienceathome.com/rust-and-machine-learning-2-with-luca-palmieri-ep-108/ Rust and machine learning #2 with Luca Palmieri (Ep. 108)]<br>
* [https://datascienceathome.com/rust-and-machine-learning-3-with-alec-mocatta-ep-109/ Rust and machine learning #3 with Alec Mocatta (Ep. 109)]<br>
* [https://datascienceathome.com/rust-and-machine-learning-4-practical-tools-ep-110/ Rust and machine learning #4: practical tools (Ep. 110)]<br>
* [https://datascienceathome.com/machine-learning-in-rust-amadeus-with-alec-mocatta-rb-ep-127/  Machine Learning in Rust: Amadeus with Alec Mocatta (Ep. 127)]<br>
* [https://datascienceathome.com/rust-and-deep-learning/ Rust and deep learning with Daniel McKenna (Ep. 135)]<br>
* [https://datascienceathome.com/is-rust-flexible-enough-for-a-flexible-data-model-ep-137/ Is Rust flexible enough for a flexible data model? (Ep. 137)]<br>
* [https://datascienceathome.com/pandas-vs-rust-ep-144/ Pandas vs Rust (Ep. 144)]<br>
* [https://datascienceathome.com/apache-arrow-ballista-and-big-data-in-rust-with-andy-grove-ep-145/ Apache Arrow, Ballista and Big Data in Rust with Andy Grove (Ep. 145)]<br>
* [https://datascienceathome.com/polars-the-fastest-dataframe-crate-in-rust-ep-146/ Polars: the fastest dataframe crate in Rust (Ep. 146)]<br>
* [https://datascienceathome.com/apache-arrow-ballista-and-big-data-in-rust-with-andy-grove-rb-ep-160/ Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)]<br>


==ИСТОЧНИКИ==
==ИСТОЧНИКИ==
* [https://dzen.ru/a/YnY7nBxvdEJtsFTu Огромный респект Автору]
* [https://dzen.ru/a/YnY7nBxvdEJtsFTu Огромный респект Автору]

Текущая версия от 19:34, 23 мая 2023

ВВЕДЕНИЕ

Эта статья содержит список библиотек машинного обучения, написанных на Rust.
Представляет собой сборник репозитариев GitHub, блогов, книг, уроков, форумов, статей.
Статья разбита на несколько основных категорий библиотек и алгоритмов. В статье нет библиотек,
которые больше не поддерживаются, а так же почти нет небольших библиотек, которые давно не обновлялись.

ЛИНЕЙНАЯ АЛГЕБРА

  • Большинство пакетов в списке используют ndarray или std::vec.

ИНСТРУМЕНТЫ ПОДДЕРЖКИ

  • Jupyter Notebook
  • evcxr может обрабатывать как Jupyter Kernel или REPL.

Эти библиотеки нужны для обучения алгоритмов и проверки гипотез машинного обучения.

РАБОТА С ВИЗУАЛИЗАЦИЕЙ

  • Список полезных ресурсов для визуализации данных.


  • ASCII line graph:


  • Примеры:


  • Дата-фреймы:

ОБРАБОТКА ИЗОБРАЖЕНИЙ

  • Для обработка изображений вам стоит попробовать библиотеку image-rs.

Здесь приведены такие алгоритмы, как линейные преобразования, подобное есть и в других библиотеках.

ОБРАБОТКА ЕСТЕСТВЕННОГО ЯЗЫКА ИЛИ ПРЕДВАРИТЕЛЬНАЯ ОБРАБОТКА

ГРАФЫ

AutoML

РАБОЧИЕ ПОТОКИ

ВЫЧИСЛЕНИЯ НА GPU С ПОМОЩЬЮ RUST

SKLEARN И ПОДОБНЫЕ БИБЛИОТЕКИ

  • Библиотеки поддерживают следующие алгоритмы:
Linear Regression
Logistic Regression
K-Means Clustering
Neural Networks
Gaussian Process Regression
Support Vector Machines
kGaussian Mixture Models
Naive Bayes Classifiers
DBSCAN
k-Nearest Neighbor Classifiers
Principal Component Analysis
Decision Tree
Support Vector Machines
Naive Bayes
Elastic Net

СТАТИСТИКА

ГРАДИЕНТНЫЙ БУСТИНГ(Gradient Boosting)

НЕЙРОННЫЕ СЕТИ

  • Tensorflow и PyTorch являются наиболее распространенными библиотеками для построения нейронных сетей.

ГРАФОВЫЕ МОДЕЛИ

НЕЙРОЛИНГВИСТИЧЕСКОЕ ПРОГРАММИРОВАНИЕ

РЕКОМЕНДАТЕЛЬНЫЕ СИСТЕМЫ

РАБОТА С ТЕКСТОМ

АЛГОРИТМЫ ПОИСКА БЛИЖАЙШИХ СОСЕДЕЙ

ОБУЧЕНИЕ С ПОДКРЕПЛЕНИЕМ

ОБУЧЕНИЕ С УЧИТЕЛЕМ

ОБУЧЕНИЕ БЕЗ УЧИТЕЛЯ

СТАТИСТИЧЕСКИЕ МОДЕЛИ

ЭВОЛЮЦИОННЫЕ АЛГОРИТМЫ

ДРУГИЕ ПРОЕКТЫ

БЛОГИ

ОБУЧЕНИЕ

ПРИКЛАДНЫЕ РЕСУРСЫ

ФОРУМЫ

КНИГИ

-- 2019/12/10, Joydeep BhattacharjeeWrite machine learning algorithms in Rust
- Use Rust libraries for different tasks in machine learning
- Create concise Rust packages for your machine learning applications
- Implement NLP and computer vision in Rust
- Deploy your code in the cloud and on bare metal servers

--

-- 2021/9/3, Shahin RostamiPlotting with Plotters and Plotly
- Operations with ndarray
- Descriptive Statistics
- Interactive Diagram
- Visualisation of Co-occurring Types
- download source code and dataset

ВИДЕО УРОКИ

Подкасты

DATA SCIENCE AT HOME:

ИСТОЧНИКИ